The existing calculation methods for the number of agricultural surplus labor have a common flaw,that is,they can not reflect the impact of technical efficiency changes in agricultural production on the surplus labor....The existing calculation methods for the number of agricultural surplus labor have a common flaw,that is,they can not reflect the impact of technical efficiency changes in agricultural production on the surplus labor. Based on the basic principle of stochastic frontier production function,this paper calculates the agricultural production technical efficiency of various provinces,and selects the province with the highest technical efficiency to assume that its agricultural labor is fully utilized,and there is no agricultural surplus labor. With the ratio of agricultural labor number to agricultural output value in this province as a reference,this paper calculates the number of agricultural surplus labor in other provinces. This calculation method makes up for the shortcomings of the existing calculation methods; it reflects the relationship between the number of agricultural surplus labor and production technical efficiency.展开更多
Stochastic frontier production function approach is adopted, 93 farmer samples have been collected, pure efficiency, technical efficiency, technical change and scale efficiency and the institutional contribution have ...Stochastic frontier production function approach is adopted, 93 farmer samples have been collected, pure efficiency, technical efficiency, technical change and scale efficiency and the institutional contribution have been calculated. The results indicated that increasing productivity is the sole measurement to reduce poverty, institution and technical change are the two key factors. Therefore, stable institution, improving technical changes are required. At present, it is urgent to make technical progre...展开更多
This study attempts to reconcile data envelopment analysis (DEA) with the production function approach in economics. We examine not only the inputs of capital and labor, but also the ranges of these inputs in producti...This study attempts to reconcile data envelopment analysis (DEA) with the production function approach in economics. We examine not only the inputs of capital and labor, but also the ranges of these inputs in production process steps, and endogenously derive a Leontief production function. The Leontief production functions shift northeasterly owing to mechanization, which is the replacement of labor inputs by capital inputs in some steps. Consequently, we describe the efficient frontier as the convex hull of the Leontief production functions. Furthermore, we consider the possibility of efficient production below the efficient frontier.展开更多
The impact of inputs on farm production growth was evaluated by analyzing the economic data of the upper and middle parts of the Yellow River basin, China for the period of 1980-1999. Descriptive statistics were emplo...The impact of inputs on farm production growth was evaluated by analyzing the economic data of the upper and middle parts of the Yellow River basin, China for the period of 1980-1999. Descriptive statistics were employed to characterize the temporal trends and spatial patterns in farm production and five pertinent inputs of cultivated cropland, irrigation ratio, agricultural labor, machinery power and chemical fertilizer. Stochastic frontier production function was applied to quantify the dependence of the farm production on these inputs. The growth of farm production was decomposed to reflect the contributions by input growths and change in total factor productivity.. The change in total factor productivity was further decomposed into the changes in technology and in technical efficiency. The gross value of farm production in the region of study increased by 1.6 fold during 1980-1999. Among the five selected farm inputs, machinery power and chemical fertilizer increased by 1.8 and 2.8 fold, respectively. The increases in cultivated cropland, irrigated cropland, and agricultural labor were all less than 0.16 fold. The growth in the farm production was primarily contributed by the increase in the total factor productivity during 1980-1985, and by input growths after 1985. More than 80% of the contributions by input growths were attributed to the increased application of fertilizer and machinery. In the change of total factor productivity, the technology change dominated over the technical efficiency change in the study period except in the period of 1985-1990, implying that institution and investment played important roles in farm production growth. There was a decreasing trend in the technical efficiency in the region of study, indicating a potential to increase farm production by improving the technical efficiency in farm activities. Given the limited natural resources in the basin, the results of this study suggested that, for a sustainable growth of farm production in the area, efforts should be directed to technology progress and improvement in technical efficiency in the use of available resources.展开更多
Elevation is one of many components that influence agriculture, and this in turn affects the level of both inputs and outputs of farmers. This article focuses on the productivity and technical efficiency of 100 cocoa ...Elevation is one of many components that influence agriculture, and this in turn affects the level of both inputs and outputs of farmers. This article focuses on the productivity and technical efficiency of 100 cocoa farms using cross-sectional data from areas ranging from 190 to 1021 m above sea level which were classified as low, medium, and high elevation in Davao City, considered as the chocolate capital of the Philippines. Using stochastic frontier analysis, the results showed that the cost of inputs per ha and the number of cocoa trees per ha significantly increase yield. Farms at high elevations were less technically efficient, as this entails lower temperatures and increased rainfall, and cocoa farming in those areas and conditions can be more challenging, especially with changes in farming practices, terrain, and distance to markets. Other significant variables were age of cocoa farms, married farmers, and age of the farmers. Older farms may be more developed, farmers who are married benefit from their spouses being able to readily contribute as farm labor, and lastly, older farmers' inefficiency may likely stem from nonadaptation of newer farming practices. With an average technical efficiency of 0.61, 0.63, and 0.26 in low, medium, and high elevation areas, respectively, farmers therefore have an incentive to improve farm practices and consider topographical variations found in high elevation areas. Recommendations for the improvement of technical efficiency of cocoa farms are better connectivity to markets, enhancing farm practices, and continuation and improvement of government programs on cocoa with an added emphasis on research. For farmers in high elevation areas, mitigating solutions such as sustainable agriculture practices and ecolabelling are key to improving efficiency and minimizing the potential negative impact on upland farming systems. Moreover, such adaptation measures may also contribute to sustainability of cocoa farming in high elevation areas.展开更多
Based on micro survey data of 344 rapeseed farmers in 19 rapeseed counties of Hubei Province,with the aid of stochastic frontier production function model and efficiency loss model,this paper analyzed basic production...Based on micro survey data of 344 rapeseed farmers in 19 rapeseed counties of Hubei Province,with the aid of stochastic frontier production function model and efficiency loss model,this paper analyzed basic production situations,demographic characteristics of rapeseed farmers,technical efficiency loss,and main influencing factors. In Hubei Province,there are mainly following problems in rapeseed production: serious aging of rapeseed farmers; relatively scarce labors; the middle-aged and old farmers have higher technical efficiency level; with increase in farmer age,their technical efficiency firstly declines and then rises. In view of these situations,it came up with recommendations including raising educational level of rapeseed farmers to realize large scale economy and effectively reduce technical efficiency loss,and local government,specialized associations and agricultural machinery extension departments should provide proper technical guidance according to demands of farmers to reduce technical efficiency loss.展开更多
基金Supported by the Fundamental Research Funds for Central Universities(SWU1409313)Fund Project for the Enterprise Management Cultivation Disciplines,Rongchang Campus,Southwest University(RCQG207001)
文摘The existing calculation methods for the number of agricultural surplus labor have a common flaw,that is,they can not reflect the impact of technical efficiency changes in agricultural production on the surplus labor. Based on the basic principle of stochastic frontier production function,this paper calculates the agricultural production technical efficiency of various provinces,and selects the province with the highest technical efficiency to assume that its agricultural labor is fully utilized,and there is no agricultural surplus labor. With the ratio of agricultural labor number to agricultural output value in this province as a reference,this paper calculates the number of agricultural surplus labor in other provinces. This calculation method makes up for the shortcomings of the existing calculation methods; it reflects the relationship between the number of agricultural surplus labor and production technical efficiency.
文摘Stochastic frontier production function approach is adopted, 93 farmer samples have been collected, pure efficiency, technical efficiency, technical change and scale efficiency and the institutional contribution have been calculated. The results indicated that increasing productivity is the sole measurement to reduce poverty, institution and technical change are the two key factors. Therefore, stable institution, improving technical changes are required. At present, it is urgent to make technical progre...
文摘This study attempts to reconcile data envelopment analysis (DEA) with the production function approach in economics. We examine not only the inputs of capital and labor, but also the ranges of these inputs in production process steps, and endogenously derive a Leontief production function. The Leontief production functions shift northeasterly owing to mechanization, which is the replacement of labor inputs by capital inputs in some steps. Consequently, we describe the efficient frontier as the convex hull of the Leontief production functions. Furthermore, we consider the possibility of efficient production below the efficient frontier.
基金support was partially provided by the University of Connecticut Research Foundation,Storrs Agricultural Experiment Station,Chinese Academy of Sciences Outstanding Overseas Chinese Scholars Award,and the National Natural Science Foundation of China(40671071).
文摘The impact of inputs on farm production growth was evaluated by analyzing the economic data of the upper and middle parts of the Yellow River basin, China for the period of 1980-1999. Descriptive statistics were employed to characterize the temporal trends and spatial patterns in farm production and five pertinent inputs of cultivated cropland, irrigation ratio, agricultural labor, machinery power and chemical fertilizer. Stochastic frontier production function was applied to quantify the dependence of the farm production on these inputs. The growth of farm production was decomposed to reflect the contributions by input growths and change in total factor productivity.. The change in total factor productivity was further decomposed into the changes in technology and in technical efficiency. The gross value of farm production in the region of study increased by 1.6 fold during 1980-1999. Among the five selected farm inputs, machinery power and chemical fertilizer increased by 1.8 and 2.8 fold, respectively. The increases in cultivated cropland, irrigated cropland, and agricultural labor were all less than 0.16 fold. The growth in the farm production was primarily contributed by the increase in the total factor productivity during 1980-1985, and by input growths after 1985. More than 80% of the contributions by input growths were attributed to the increased application of fertilizer and machinery. In the change of total factor productivity, the technology change dominated over the technical efficiency change in the study period except in the period of 1985-1990, implying that institution and investment played important roles in farm production growth. There was a decreasing trend in the technical efficiency in the region of study, indicating a potential to increase farm production by improving the technical efficiency in farm activities. Given the limited natural resources in the basin, the results of this study suggested that, for a sustainable growth of farm production in the area, efforts should be directed to technology progress and improvement in technical efficiency in the use of available resources.
文摘Elevation is one of many components that influence agriculture, and this in turn affects the level of both inputs and outputs of farmers. This article focuses on the productivity and technical efficiency of 100 cocoa farms using cross-sectional data from areas ranging from 190 to 1021 m above sea level which were classified as low, medium, and high elevation in Davao City, considered as the chocolate capital of the Philippines. Using stochastic frontier analysis, the results showed that the cost of inputs per ha and the number of cocoa trees per ha significantly increase yield. Farms at high elevations were less technically efficient, as this entails lower temperatures and increased rainfall, and cocoa farming in those areas and conditions can be more challenging, especially with changes in farming practices, terrain, and distance to markets. Other significant variables were age of cocoa farms, married farmers, and age of the farmers. Older farms may be more developed, farmers who are married benefit from their spouses being able to readily contribute as farm labor, and lastly, older farmers' inefficiency may likely stem from nonadaptation of newer farming practices. With an average technical efficiency of 0.61, 0.63, and 0.26 in low, medium, and high elevation areas, respectively, farmers therefore have an incentive to improve farm practices and consider topographical variations found in high elevation areas. Recommendations for the improvement of technical efficiency of cocoa farms are better connectivity to markets, enhancing farm practices, and continuation and improvement of government programs on cocoa with an added emphasis on research. For farmers in high elevation areas, mitigating solutions such as sustainable agriculture practices and ecolabelling are key to improving efficiency and minimizing the potential negative impact on upland farming systems. Moreover, such adaptation measures may also contribute to sustainability of cocoa farming in high elevation areas.
文摘Based on micro survey data of 344 rapeseed farmers in 19 rapeseed counties of Hubei Province,with the aid of stochastic frontier production function model and efficiency loss model,this paper analyzed basic production situations,demographic characteristics of rapeseed farmers,technical efficiency loss,and main influencing factors. In Hubei Province,there are mainly following problems in rapeseed production: serious aging of rapeseed farmers; relatively scarce labors; the middle-aged and old farmers have higher technical efficiency level; with increase in farmer age,their technical efficiency firstly declines and then rises. In view of these situations,it came up with recommendations including raising educational level of rapeseed farmers to realize large scale economy and effectively reduce technical efficiency loss,and local government,specialized associations and agricultural machinery extension departments should provide proper technical guidance according to demands of farmers to reduce technical efficiency loss.
